Hacktoberfest 2026: los issues que los mantenedores marcaron para octubre, abiertos y aptos para principiantes. Explorar issues de Hacktoberfest

[core] Client disconnects don't cancel the model stream (per-step flow is cached) — and there is no public API to cancel an in-flight run

Abierto
  • ¿Algo no está bien?
#1,618 6 comentarios 0 reacciones 1 asignado Ver en GitHub

Los mantenedores suelen responder en 1 día

@hemasekhar-p ya está trabajando en esto.

Desde el 6/10/2026.

  • #1621 de @sangkyoonnam — abierto

Evaluación

Este issue todavía no se ha evaluado.

Descripción

needs review
Describe the Bug

When a client disconnects while an agent is streaming (e.g. the SSE consumer cancels its subscription to Runner's event flow), the underlying model call keeps running to completion. Tokens continue to be billed with no consumer attached. In one production incident the model kept generating for 3+ minutes after the client went away (observed via gateway-side logs and token metering).

The cause appears to be BaseLlmFlow.java line 530 (main at the time of writing):

Flowable<Event> currentStepEvents = runOneStep(spanContext, invocationContext).cache();

With RxJava cache(), the upstream connection is only disposed when all subscribers of the cached flow cancel. As long as any subscriber attached by the framework itself (event handling/aggregation within the invocation) is alive, a user-side cancellation cannot reach the model stream.

On top of that, there is no public API to cancel an in-flight run: neither Runner nor InvocationContext nor the session exposes a "stop generating" handle. The only way to stop a long generation is to let it finish.

To Reproduce
  1. Serve an agent behind SSE; start a streaming run with a slow/long model response (or a multi-round tool loop).
  2. Disconnect the SSE client mid-generation and dispose the event-flow subscription.
  3. Observe on the model/gateway side (or via token metering) that generation continues until the model finishes naturally.
Expected behavior

Cancelling the downstream subscription (or any public cancellation entry point) must reach the model stream: the in-flight LLM request is disposed (or aborted at the next chunk/round boundary), and no further rounds are started.

Environment
  • google/adk-java main (1.11.1-SNAPSHOT at the time of writing)
  • Spring AI bridge + SSE transport, but the cache() behavior is in core (BaseLlmFlow) and should affect any transport
Additional context

In production we could only implement "stop generating" with a cooperative cancellation protocol outside the framework: a per-run cancel flag (REST endpoint sets it) that the model-stream loop checks at every chunk and at tool-round boundaries, plus setCancellable hooks for the current round. It works, but it is entirely application-side — the framework neither propagates the cancellation nor offers a canonical way to express it.

Suggested directions (happy to discuss or contribute):

  1. Replace the unbounded cache() with cancellation-propagating semantics (e.g. publish().refCount()-style sharing, or a scoped subscription that disposes the source when the invocation ends/cancels), or
  2. Expose a first-class cancellation handle per run/invocation, and document that model loops should check it at chunk/round boundaries (cooperative cancellation), or
  3. At minimum, document the current behavior prominently — today it silently leaks billable model calls.
Lenguaje dominante
Java
Estrellas
1.7k
Forks
433
Merge medio
3 d 11 h
PR fusionados (30 d)
50

Preparar el entorno

Abrir en Codespaces

Inicia el contenedor de desarrollo del proyecto en tu navegador, con tu propia cuenta de GitHub.

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Más de google/adk-java

Todos los issues de google/adk-java

Issues similares

Más issues de Java

Recibe los nuevos issues en tu correo

Un resumen breve de issues de GitHub para principiantes.